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COVID-19 and systemic lupus erythematosus genetics: A balance between autoimmune disease risk and protection against infection [1]

['Yuxuan Wang', 'Department Of Medical', 'Molecular Genetics', 'King S College London', 'London', 'United Kingdom', 'Suri Guga', 'Kejia Wu', 'Zoe Khaw', 'Konstantinos Tzoumkas']

Date: 2022-12 

Genome wide association studies show there is a genetic component to severe COVID-19. We find evidence that the genome-wide genetic association signal with severe COVID-19 is correlated with that of systemic lupus erythematosus (SLE), having formally tested this using genetic correlation analysis by LD score regression. To identify the shared associated loci and gain insight into the shared genetic effects, using summary level data we performed meta-analyses, a local genetic correlation analysis and fine-mapping using stepwise regression and functional annotation. This identified multiple loci shared between the two traits, some of which exert opposing effects. The locus with most evidence of shared association is TYK2, a gene critical to the type I interferon pathway, where the local genetic correlation is negative. Another shared locus is CLEC1A, where the direction of effects is aligned, that encodes a lectin involved in cell signaling, and the anti-fungal immune response. Our analyses suggest that several loci with reciprocal effects between the two traits have a role in the defense response pathway, adding to the evidence that SLE risk alleles are protective against infection.

We observed a correlation between the genetic associations with severe COVID-19 and those with systemic lupus erythematosus (SLE, Lupus), and aimed to discover which genetic loci were shared by these diseases and what biological processes were involved. This resulted in the discovery of several genetic loci, some of which had alleles that were risk for both diseases and some of which were risk for severe COVID-19 yet protective for SLE. The locus with most evidence of shared association (TYK2) is involved in interferon production, a process that is important in response to viral infection and known to be dysregulated in SLE patients. Other shared associated loci contained genes also involved in the defense response and the immune system signaling. These results add to the growing evidence that there are alleles in the human genome that provide protection against viral infection yet are risk for autoimmune disease.

The outbreak of COVID-19 together with modern genotyping technologies has given us the unprecedented opportunity to investigate the genetics of response to viral infection. Recent GWAS of severe COVID-19 have shown that there is a genetic component to the variability of the clinical outcome [ 1 ]. Some of the genetic loci identified unsurprisingly point to pathways involved in the host immune response. Therefore, a comparison between the genetics of severe COVID-19 and autoimmune disease (AID) may be enlightening. In this study we compare the genetics of severe COVID-19 with those of systemic lupus erythematosus (SLE). The rationale for selecting SLE is twofold: some SLE risk alleles act to augment the interferon response (e.g. IRF5, IRF7, CXORF21-TASL); other lupus susceptibility genes act in the intracellular viral sensing (e.g. IFIH1, TLR7, RNASEH2C) pathway.

The meta-analysis identified a narrow peak of association between 10.2–10.3Mb on chromosome 12 that colocalized between the two traits ( See Fig 3B ; PP H4 = 0.95 and Table 3 , overlapped N SNP = 3,363). Both traits’ association signals colocalized with eQTLs for CLEC1A in multiple tissues (PP H4 ≥ 0.97/0.87 for eQTL colocalisation with COVID-19/SLE) in GTEx v8 data. Fig 4C displays the association in both diseases and eQTL data for heart (atrial appendage), see Fig T in S1 Text for the other eQTL colocalization. eQTL summary statistics can be seen in Table G in S1 Text . The risk allele for severe COVID-19 is also risk for SLE and is associated with reduced expression of CLEC1A. The lead variant rs7960611 is in LD with a missense variant rs2306894 (r 2 = 0.84).

We found that the genetic associations in signal-B tagged by rs34725611 and rs11085727 colocalize with a TYK2 eQTL signal in whole blood in eQTLGen [ 14 ] ( Fig 4B ) and GTEx v8 data, and adrenal gland in GTEx v8 data: PP H4 > 0.98 for colocalisation between the two traits and with all eQTL signals ( Fig N in S1 Text ). eQTL summary statistics can be seen in Table G in S1 Text , where the associated allele effects can be compared across traits and eQTL. In all cases the protective allele for SLE, which is the risk allele for severe COVID-19, increases expression. However, signal-B is also associated with altered TYK2 function as a missense variant rs2304256 (V362F, exon 8), that is in strong LD (r 2 = 0.98 in SLE data) with rs11085727, acts as a splicing eQTL. The SLE protective allele promotes inclusion of exon 8 [ 15 ], which increases TYK2 function. Thus, signal-B provides conflicting results with respect to signal-A regarding the functional impact on TYK2. To understand the role of signals A and B on gene regulation, we studied the epigenetic landscape around these two association signals ( Fig O in S1 Text ). For signal A, there was evidence for localization to enhancer chromatin marks (H3K27Ac and H3K4Me1, Fig P in S1 Text ). However, there was much less evidence for such alignment with signal-B ( Fig Q in S1 Text ). Signal-A is also observed to loop in 3D space to the promotor of PDE4A ( Fig R in S1 Text ). While we did observe other significant cis eQTLs with signal-B SNPs ( see Fig S in S1 Text ), none of them colocalized with COVID-19 or SLE signals (PP H4 < 0.20 in all cases).

The TYK2 locus has previously been found to be associated with SLE [ 4 , 8 – 12 ] and severe COVID-19 [ 1 ]. There was significant negative local genetic correlation (p-value = 1 x 10 −04 , ρ-HESS, overlapped N SNP = 2,544) at TYK2 between the two diseases. In a stepwise regression approach using summary meta-analysis data for both traits, we found a highly significant overlap between genetic association signals (overlapped N SNP = 4,720); importantly, the SLE risk alleles were protective against severe COVID-19. The locus-wide association signals in COVID-19 and SLE are compared in Fig 3A . There were two independent signals that colocalized across traits (posterior probabilities of coloc = 0.991 and 0.993), referred to arbitrarily as signal-A and signal-B in Table 2 . The top two SNPs independently associated with SLE (rs34536443 and rs34725611) are in high LD (r 2 = 0.88 and 0.97 respectively), with the two SNPs we found to be independently associated with severe COVID-19 (rs74956615 and rs11085727) being reported previously in a COVID-19 GWAS [ 1 ]. For a full set of association results for these SNPs across traits see Table F in S1 Text , where it is shown that for all SNPs the effects have reciprocal directions of effect in SLE and COVID-19 outcome. In both traits, the relatively rare variants rs34536443/rs74956615 were associated independently from the more common variants rs34725611/rs11085727 (see conditional results bJ and pJ in Table 2A and 2B ; r 2 = 0.06 and 0.09 between rs34536443 and rs34725611 and between rs74956615 and rs11085727 respectively in the EUR SLE data, r 2 = 0.08 and 0.07 in the 1000 genomes EUR data).

We performed a cross-trait meta-analysis that included an analysis to highlight opposing effects (see Material and Methods , overlapped N SNPs = 1,559,546). Manhattan plots from the meta-analyses can be seen in Fig 2 . There were 15 loci that had genome-wide significant evidence of (p-values < 5 x 10 −08 , Table 1 ), the very significant p-values at the TYK2 locus in the lower plot ( Fig 2 ) highlights the negative correlation at this locus. There were six association signals in five of these loci with colocalization probabilities (PP H4 ) greater than 0.8 and three of these, implicating CLEC1A, TYK2 and PDE4A, had PP H4 > 0.95 ( Table 1 ). The TYK2-PDE4A locus had opposing direction of effect across the two diseases and the other 4 loci (CLEC1A, IL12B, PLCL1-RFTN2, and MIR146A) had agreement in direction of effect. Though genome-wide significant evidence were found in the other 10 loci, there was relatively weak evidence for colocalization. Two well-known SLE associated loci, IRF8 and TNFSF4, showed evidence of significant association in the opposing effect meta-analysis with some evidence for colocalisation of shared signals at both loci (IRF8 PP H4 = 0.36, TNFSF4 PP H4 = 0.37; Tables C and D and Fig A in S1 Text ). LocusZoom plots for all other loci can be seen in Figs B-L in S1 Text . A pathway analysis showed that there was an enrichment of genes in defense response, cytokine-mediated signaling and type I interferon signaling pathway with over half the genes being included in one or more pathways ( Table E and Fig M in S1 Text ) .

To investigate the shared genetics between SLE and severe COVID-19, we ran a genome-wide genetic correlation analysis between ancestry matched SLE and severe COVID-19 association data. The SLE data comprised a meta-analysis of three European GWASs [ 2 – 4 ] (N cases = 5,734, N controls = 11,609, Table A in S1 Text ) and for the COVID-19 we used the GenOMICC release 1 European data [ 1 ] (critically ill patients with COVID-19 vs. ancestry-matched control individuals from UK Biobank, N cases = 1,676, N controls = 8,380, Table A in S1 Text ). We found the two traits to be genetically correlated (r g = 0.56, s.e. = 0.16, p = 3 x 10 −04 ). To identify which regions were driving this correlation we ran a local genetic correlation analysis that included Immunochip European data [ 5 ] in the SLE meta-analysis (additional N cases = 3,568, N controls = 11,245, Table A in S1 Text ). This identified multiple loci with both positive and negative correlation of which the TYK2 locus was the most significantly correlated (p-value = 1 x 10 −04 , Table B in S1 Text ). This gene encodes a kinase that regulates transduction of IFN-I signaling. An overview of GWAS data used in the study is illustrated in Fig 1 and Table A in S1 Text .

Discussion

Our results indicate that there are shared genetic effects between the autoimmune disease SLE and the clinical consequences of COVID-19. The locus with the most evidence of shared effects was the Janus kinase (JAK), TYK2, that promotes IL-12 and IFN-I signaling. Here there are two separate genetic association signals (designated A and B) shared between severe COVID-19 and SLE. Importantly for both, the genetic factors for SLE risk mitigate the outcome following SARS-Cov2 infection. In seeking to uncover the mechanisms underlying these relationships it was apparent that the functional effects of the risk alleles are complex. Signal-A at TYK2 is likely driven by a coding P1104A variant (rs34536443) whose COVID-19 risk allele has been shown to impair TYK2 target phosphorylation [13]. This is further supported by the therapeutic effect of a TYK2 inhibitor in psoriasis [18], and by observed risk in other infectious disease such as tuberculosis where it has been found that homozygosity for the minor allele (C) of rs34536443 is risk, in line with severe COVID-19, and strongly impairs IL-23 signaling in T cells and IFN-γ production in PBMC [19,20]. Signal-A, led by rs34536443, was also found to colocalize with an eQTL for nearby PDE4A, which encodes a phosphodiesterase that regulates cAMP. This enzyme has multiple potential roles, however PDE4A inhibitors have been shown to have anti-inflammatory activity and are being studied in AID and inflammatory lung diseases [21]. The severe COVID-19 risk alleles are associated with decreased expression of PDE4A, while they are protective for SLE. The PDE4A eQTL cell type is heterogeneous however and the relevance to SLE is unclear. Signal-B includes another missense variant in TYK2, namely rs2304256 (V362F) in exon 8, but this also acts as a splicing mutation and the missense variant is missing from the spliced transcript. The severe COVID-19 risk allele promotes inclusion of exon 8 in TYK2 that is essential for TYK2 binding to cognate receptors [15]. Therefore signal-B comprises evidence for two functional effects with respect to COVID-19 risk alleles, one of which increases function of TYK2 through altered splicing (rs2304256 (V362F)) and one that is correlated with increased expression of TYK2 (rs11085727). It may be that the overall reduction of TYK2 activity caused by the COVID-19 risk alleles in signal-A evokes a compensatory effect on overall gene expression, which is designed to mitigate the deleterious effect of the missense variants–an example of regulatory variants modifying the penetrance of coding variants [15,22]. This conjecture is supported by the lack of epigenetic marks in the signal-B region of TYK2.

The severe COVID-19 risk allele for signal-B at TYK2 is associated with reduced SERPING1 and CXCL10 protein expression, implying that the minor allele at signal-B in the TYK2 locus reduces some aspect of TYK2 function. CXCL10 (IP-10) is a chemokine that acts on Th1 cells and is key regulator of the cytokine storm immune response to COVID-19 infection [23]. SERPING1, an inhibitor of complement 1 (C1-inh), is known to be reduced by infection and this reduction correlates with more severe COVID-19 [24]. Therefore genetic predisposition to low SERPING1 expression may increase risk for COVID-19 through the same dynamics as reduced levels due to infection. This and the effect of reduced levels of CXCL10 are likely just two examples of altered IFN induced activity that affects risk for disease.

We found agreement in direction of effect of association in CLEC1A. CLEC1A is interesting as C-type Lectin receptors are involved in fungal recognition and fungal immunity. Genetic variation in CLEC1A is a risk factor for the development of Aspergillosis in immunosuppression [25]. CLEC1A is a negative regulator of dendritic cells [26]. Therefore the SLE and severe COVID-19 risk allele, being associated with reduced expression of CLEC1A, would be expected to exert a pro-inflammatory effect. We also found agreement in direction of effect of associations in 3 other loci (IL12B, PLCL1-RFTN2, MIR146A) that showed relatively strong evidence of colocalization. The modest p-values and relatively high colocalisation possibilities support them as good candidates to follow up in larger studies. At both IRF8 and TNFSF4 the evidence for association in severe COVID is moderate yet the signals do show some evidence of colocalizing with opposing effects in SLE. With prominent roles in the pro-inflammatory IFN response these two loci should be a focus when larger data in severe COVID-19 are available. IRF8 provides more evidence that the IFN pathway is important in the balance between SLE risk and infection as mutations that impair IRF8 transcriptional activity have been found to cause immunodeficiency [27]. Interferons constitute one of the main means of host defense against viruses and hence have been well studied in the context of COVID-19 [28–30]. In SLE, evidence for interferon activity is present in about half of the patients and is often present in those with more severe disease [31–33]. Although elevated interferon has been implicated in other AID, the role is prominent in SLE. This has been exploited with therapeutic agents designed to antagonize type I interferon activity showing benefit in SLE [34]. Parallels between SLE and viral infection extend beyond interferon activation though. As stated above there are SLE risk genes that act in the intracellular viral sensing pathways. SLE is characterized by an immune response against host nucleic acids. The means by which the immune system loses tolerance to these structures appears to involve aberrant exposure of self through the pathways that are designed to sense foreign nucleic acids, as happens during viral infection [35]. Further investigation into the genetic correlation between SLE and severe COVID-19 will help explain the genetic basis of both diseases, which may be in part due to variation in response to viral infection. Risk alleles for SLE, that are also risk for severe COVID-19, may persist in the population due to protective effects against other exposures such as fungal infection. The opposing effects we find at the TYK2 locus is compatible with the hypothesis that there are alleles in the general population that, while represent a risk for SLE, persist possibly due to an innate immune protection against pathogens [36–41] including viruses.

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[1] Url: https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1010253

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